[1] 林伟伟, 朱朝悦. 面向大规模云资源调度的可扩展分布式调度方法[J]. 计算机工程与科学, 2015, 37(11): 1997-2005.

    Lin W W, Zhu C Y. A scalable distributed scheduling method for large-scale cloud resources[J]. Computer Engineering and Science, 2015, 37(11): 1997-2005.

[2] 郭琪瑶, 朱范德. 基于蚁群算法和蛙跳算法的云计算资源调度算法[J]. 科技通报, 2017, 33(5): 167-170.

    Guo Q Y, Zhu F D. Cloud computing resource scheduling algorithm based on ant colony algorithm and leapfrog algorithm[J]. Bulletin of Science and Technology, 2017, 33(5): 167-170.

[3] 李建锋, 彭舰. 云计算环境下基于改进遗传算法的任务调度算法[J]. 计算机应用, 2011, 31(1): 184-186.

    Li J F, Peng J. Task scheduling algorithm based on improved genetic algorithm in cloud computing environment[J]. Journal of Computer Applications, 2011, 31(1): 184-186.

[4] 黄俊, 王庆凤, 刘志勤, 等. 基于资源状态蚁群算法的云计算任务分配[J]. 计算机工程与设计, 2014, 35(9): 3305-3309.

    Huang J, Wang Q F, Liu Z Q, et al. Cloud task scheduling based on resource state ant colony optimization[J]. Computer Engineering and Design, 2014, 35(9): 3305-3309.

[5] 吕燕兵, 王静宇, 吴金明. 云计算资源负载均衡调度优化算法研究[J]. 内蒙古科技大学学报, 2017, 36(2): 181-186.

    Lü Y B, Wang J Y, Wu J M. Research on load-balance resource scheduling algorithm in cloud computing[J]. Journal of Inner Mongolia University of Science and Technology, 2017, 36(2): 181-186.

[6] 魏赟, 陈元元. 基于改进蚁群算法的云计算任务调度模型[J]. 计算机工程, 2015, 41(2): 12-16.

    Wei Y, Chen Y Y. Cloud computing task scheduling model based on improved ant colony algorithm[J]. Computer Engineering, 2015, 41(2): 12-16.

[7] 华夏渝, 郑骏, 胡文心. 基于云计算环境的蚁群优化计算资源分配算法[J]. 华东师范大学学报(自然科学版), 2010( 1): 127- 134.

    Hua XY, ZhengJ, Hu WX. Ant colony optimization algorithm for computing resource allocation based on cloud computing environment[J]. Journal of East China Normal University(Natural Science), 2010( 1): 127- 134.

[8] 张浩荣, 陈平华, 熊建斌. 基于蚁群模拟退火算法的云环境任务调度[J]. 广东工业大学学报, 2014, 31(3): 77-82.

    Zhang H R, Chen P H, Xiong J B. Task scheduling algorithm based on simulated annealing ant colony algorithm in cloud computing environment[J]. Journal of Guangdong University of Technology, 2014, 31(3): 77-82.

[9] 张焕青, 张学平, 王海涛, 等. 基于负载均衡蚁群优化算法的云计算任务调度[J]. 微电子学与计算机, 2015, 32(5): 31-35, 40.

    Zhang H Q, Zhang X P, Wang H T, et al. Task scheduling algorithm based on load balancing ant colony optimization in cloud computing[J]. Microelectronics & Computer, 2015, 32(5): 31-35, 40.

[10] 左利云, 左利锋. 云计算中基于预先分类的调度优化算法[J]. 计算机工程与设计, 2012, 33(4): 1357-1361.

    Zuo L Y, Zuo L F. Cloud computing scheduling optimization algorithm based on reservation category[J]. Computer Engineering and Design, 2012, 33(4): 1357-1361.

[11] AgarwalM, Srivastava G M S. A genetic algorithm inspired task scheduling in cloud computing[C]∥2016 International Conference on Computing, Communication and Automation (ICCCA), April 29-30, 2016, Greater Noida, India. New York: IEEE, 2016: 364- 367.

[12] Wang TT, Liu ZB, ChenY, et al. Load balancing task scheduling based on genetic algorithm in cloud computing[C]∥2014 IEEE 12th International Conference on Dependable, Autonomic and Secure Computing, August 24-27, 2014, Dalian, China. New York: IEEE, 2014: 146- 152.

[13] Sheng XD, LiQ. Template-based genetic algorithm for QoS-aware task scheduling in cloud computing[C]∥2016 International Conference on Advanced Cloud and Big Data (CBD), August 13-16, 2016, Chengdu, China. New York: IEEE, 2016: 25- 30.

[14] Song WZ, YangB, Zhao XH, et al. A fast and scalable supervised topic model using stochastic variational inference and MapReduce[C]∥2016 IEEE International Conference on Network Infrastructure and Digital Content (IC-NIDC), September 23-25, 2016, Beijing, China. New York: IEEE, 2016: 94- 98.

[15] Chen X, Song W F, Li Z G. Research of resource scheduling based on ACA-GA in the cloud computing[J]. International Journal of Grid and Distributed Computing, 2016, 9(6): 1-12.